Unlike classical computers, quantum machines leverage the principles of quantum physics to process information in fundamentally different ways. Experts estimate that within the next 10 to 20 years, sufficiently powerful quantum computers may be capable of cracking widely used encryption — potentially reducing what would take today’s best systems billions of years to break down to mere hours or days.

Cryptography at Risk

Public-key cryptography — the backbone of secure email, online banking, and federal systems — is particularly at risk. A future quantum computer could dismantle the mathematical foundations of these protections, enabling unauthorized access to sensitive data and critical services. Even more concerning, adversaries may already be collecting encrypted data today with the intention of decrypting it later when quantum capabilities are available — a tactic known as “harvest now, decrypt later.”

Despite the urgency, the GAO’s assessment finds that the U.S. does not yet have a fully developed national strategy to address this emerging threat. Federal agencies have produced a patchwork of guidance and best practices for transitioning to quantum-resilient systems, but these efforts lack coordination and clearly defined milestones — particularly for critical infrastructure outside direct government control.

Leadership Gaps and Strategic Shortfalls

GAO notes that no central federal authority is currently responsible for overseeing a comprehensive quantum cybersecurity strategy. To fill this strategic gap, the report recommends that the Office of the National Cyber Director take the lead in coordinating efforts across government and ensure that agencies clearly understand their roles in preparing for a post-quantum future.

As experts continue developing and standardizing post-quantum cryptography — encryption designed to resist quantum attacks — federal and private sectors alike are being urged to accelerate planning and implementation to safeguard systems before quantum threats materialize.

Material by Yana Petrova

Image: Freepik

IBM has introduced a suite of new technologies aimed at scaling enterprise AI across hybrid environments, as announced today at its annual THINK conference. This move reinforces IBM’s commitment to breaking down barriers to AI deployment with integrated solutions that unify data, orchestrate AI agents, and simplify enterprise operations.

With over one billion applications projected to emerge by 2028, businesses are under increasing pressure to streamline operations across fragmented systems. IBM is responding with hybrid technologies, enhanced agent capabilities, and the consulting expertise of IBM Consulting, aiming to help clients accelerate AI adoption and realize measurable business value.

Arvind Krishna, Chairman and CEO of IBM

“The era of AI experimentation is over,”

said Arvind Krishna, Chairman and CEO of IBM.

“Today’s competitive advantage comes from purpose-built AI integration that drives measurable business outcomes.”

Enterprise AI Agents Powered by watsonx Orchestrate

Central to IBM’s announcement is the expanded functionality of watsonx Orchestrate, designed to help businesses create, deploy, and manage AI agents across a wide array of enterprise tools.

Key features include:

• Agent Builder: Enables users to create custom AI agents in under five minutes using no-code to pro-code tools.
• Pre-built Domain Agents: Ready-to-use agents tailored for HR, sales, procurement, and more.
• Wide Integration: Supports over 80 leading enterprise applications, including solutions from Adobe, AWS, Microsoft, Oracle, Salesforce Agentforce, SAP, ServiceNow, and Workday.
• Agent Orchestration: Coordinates multi-agent workflows and tools across vendors.
• Agent Observability: Provides monitoring, guardrails, and lifecycle governance.

IBM also unveiled the Agent Catalog, offering access to over 150 agents and tools co-developed with partners like Box, Mastercard, Symplistic.ai, 11x, and others. Sample integrations include a Salesforce-native prospecting agent and a conversational HR agent for Slack.

Tackling Integration Challenges with webMethods Hybrid Integration

A common obstacle to enterprise AI adoption is integration complexity. IBM is addressing this with the launch of webMethods Hybrid Integration, a solution for automating workflows across applications, APIs, partners, and clouds.

According to a Forrester Total Economic Impact (TEI) study, organizations using webMethods realized:

• 176% ROI over three years
• 40% reduction in downtime
• Up to 67% time savings on project execution
• Improved ease of use, security, and visibility

This integration technology complements IBM’s existing automation offerings and is enhanced by collaborations with HashiCorp, including integrations with Terraform and Vault, to support secure, scalable hybrid cloud operations.

Unlocking the Value of Unstructured Data

Unstructured data—such as contracts, spreadsheets, and presentations—represents a largely untapped asset in enterprise AI. IBM is advancing watsonx.data to help organizations activate this data with greater accuracy.

Highlights include:

• Open Data Lakehouse: Now with data fabric features like lineage tracking and governance.
• watsonx.data integration: A unified tool for orchestrating data pipelines across formats.
• watsonx.data intelligence: AI-driven tools for deep insights from unstructured data.

Early testing indicates watsonx.data enables up to 40% more accurate AI compared to traditional retrieval-augmented generation (RAG) methods.

In support of this strategy, IBM recently announced plans to acquire DataStax, a leader in unstructured data handling for generative AI. Additionally, watsonx is now integrated with Meta’s Llama Stack, further enhancing its generative AI capabilities.

IBM’s Content-Aware Storage (CAS) is also now available on IBM Fusion, with support for IBM Storage Scale arriving in Q3. CAS enables contextual processing of unstructured data to speed up AI inferencing.

Infrastructure for AI at Scale: Introducing IBM LinuxONE 5

To support high-performance AI workloads, IBM introduced IBM LinuxONE 5, its most secure and powerful Linux platform to date. It can process up to 450 billion AI inference operations per day.

Innovations include:

• Telum II AI Processor & IBM Spyre Accelerator: High-speed processing for generative AI, with Spyre available in late 2025.
• Confidential Containers & Quantum-Safe Encryption: Advanced security for sensitive workloads.
• Cost and Energy Efficiency: Compared to x86 systems, LinuxONE 5 can lower total cost of ownership by up to 44% over five years.

IBM also expanded partnerships with AMD, Intel, CoreWeave, and NVIDIA to deliver new compute and storage solutions for AI-driven applications.

The Road Ahead

IBM’s latest announcements represent a strategic push toward operationalizing AI at enterprise scale through modular, secure, and hybrid-ready technologies. As businesses move from AI experimentation to enterprise-wide adoption, IBM aims to be the infrastructure backbone enabling that transformation.

Image: IBM video